2006 Fiscal Year Final Research Report Summary
Development of Automated Damage Detection Technique for Urban Disasters Using High-resolution Satellite Images
| Project/Area Number |
17310090
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Chiba University |
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Principal Investigator |
YAMAZAKI Fumio Chiba University, Faculty of Engineering, Professor, 工学部, 教授 (50220322)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAI Shouichi Chiba University, Faculty of Engineering, Professor, 工学部, 教授 (90292664)
MATSUOKA Masashi National Institute of Earth Science and Disaster Mitigation, EDM, Team Leader, チームリーダー (80242311)
MARUYAMA Yoshihisa Chiba University, Faculty of Engineering, Research Associate, 工学部, 助手 (70397024)
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| Project Period (FY) |
2005 – 2006
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| Keywords | High-resolution satellite images / Earthquake damage / Tsunami / The 2004 Indian Ocean tsunami / The 2006 Central Java earthquake / Optical sensors / object-based image segmentation and classification technique / Building damage |
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| Research Abstract |
In this study, automated damage detection technique was developed using high-resolution satellite images. Comparisons between pre- and post-event images were effective to show the affected areas by natural disasters, e.g., earthquakes and tsunami. In addition that, the technique to identify damaged areas only from the post-event images was also considered in this study. The damage detection technique was developed using the high-resolution satellite images captured in the 2004 Indian Ocean earthquake and the 2006 Central Java earthquake, and aerial photographs taken after the 2004 Mid-Niigata earthquake.
To detect the affected areas by Indian Ocean tsunami in 2004, the normalized difference vegetation index (NDVI), soil index (NDSI), and water index (NDWI) were compared between the pre- and post-event images. The digital elevation model was also utilized to reveal the damaged areas.
As for the 2006 Central Java earthquake, object-based image segmentation and classification technique as well as pixel-based technique have been applied to the satellite images. According to the results, the object-based image segmentation and classification technique was effective to identify the damaged areas especially for high-resolution satellite images.
The damaged sections of expressways were detected by image processing using the aerial photographs in the 2004 Mid-Niigata earthquake. The overturning ratio of tombstones in a cemetery was estimated based on an image analysis of aerial photographs.
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